Biology subjects

Socha, K.

Publications and source records attributed to Socha, K..

4 recordsLinked to original sources

bioRxiv2026

Chronoecological interactions: Temporal niche-switching by black-striped mice after agonistic food competition with a dominant sympatric mouse species

When novel nutrient-rich food sources become available to species sharing the same natural habitat, interspecies competition may arise, yielding insights into the ecological and social dynamics of the observed species. Here, we investigated food consumption patterns, and consequent social interactions, by two sympatric species of mice in response to a novel nutrient-rich food source. By deploying, in the mices natural habitat, baited video-monitored chambers, we collected, over a 5-month period, 1805 observations of food visiting by Apodemus agrarius and Apodemus flavicollis. We also documented interspecific encounters, with 86.7% of the cases showing agonism. In these interspecies agonistic encounters, A. flavicollis was always the initiator of agonism, attacking within 2 sec in 92.3% of the cases, and being dominant over A. agrarius in 84.6%. Analysis of food visiting behavior revealed that, initially, both species preferred nocturnality. However, after the interspecies fights, A. agrarius switched its temporal preference to diurnality, leading to temporal niche segregation between the two species and a significant reduction of interspecies encounters. Moreover, A. agrarius demonstrated hour-specific avoidance of A. flavicollis, visiting significantly less in hours with A. flavicollis compared to hours without. Through temporal niche switching, A. agrarius managed to access the food source safely, without fights. In contrast, A. flavicollis remained consistently nocturnal across the entire study. Notably, our study presents the first 24h foraging actogram for free-living rodents. Moreover, while rodent interspecific competition is a well-known phenomenon, most of what we know about it comes from indirect observations. Direct observations of rodent interspecific interactions in nature are rare. Our work is the first direct (video-monitored) observation of temporal switch-inducing interspecies interactions in nature. As free-living rodents are currently considered a major model system for the study of interspecific competition, these results may offer precious insights for a better understanding of social dynamics, especially in asymmetric relationships. Furthermore, our findings highlight the significance of considering temporal dynamics in studies of interspecific interactions.

animal behavior and cognition↗

bioRxiv2020

A standardized and reproducible method to measure decision-making in mice

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We designed a task for head-fixed mice that combines established assays of perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be successfully reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path towards achieving reproducibility in neuroscience through collaborative open-science approaches.

neuroscience↗

bioRxiv2018

Characterizing the nonlinear structure of shared variability in cortical neuron populations using neural networks

Sensory neurons often have variable responses to repeated presentations of the same stimulus, which can significantly degrade the information contained in those responses. Such variability is often shared across many neurons, which in principle can allow a decoder to mitigate the effects of such noise, depending on the structure of the shared variability and its relationship to sensory encoding at the population level. Latent variable models offer an approach for characterizing the structure of this shared variability in neural population recordings, although they have thus far typically been used under restrictive mathematical assumptions, such as assuming linear transformations between the latent variables and neural activity. Here we leverage recent advances in machine learning to introduce two nonlinear latent variable models for analyzing large-scale neural recordings. We first present a general nonlinear latent variable model that is agnostic to the stimulus tuning properties of the individual neurons, and is hence well suited for exploring neural populations whose tuning properties are not well characterized. This motivates a second class of model, the Generalized Affine Model, which simultaneously determines each neurons stimulus selectivity and a set of latent variables that modulate these stimulus responses both additively and multiplicatively. While these approaches can detect general nonlinear relationships in shared neural variability, we find that neural activity recorded in anesthetized primary visual cortex (V1) is best described by a single additive and single multiplicative latent variable, i.e., an \"affine model\". In contrast, application of the same models to recordings in awake macaque prefrontal cortex discover more general nonlinearities to compactly describe the population response variability. These results thus demonstrate how nonlinear latent variable models can be used to describe population variability, and suggest that a range of methods is necessary to study different brain regions under different experimental conditions.

neuroscience↗

bioRxiv2018

Behavioral response to visual motion impacts population coding in the mouse visual thalamus

Visual motion is a ubiquitous component of animals sensory experience and its encoding is critical for navigation and movement. Yet its impact on behavior and neural coding is not well understood. Combining pupillometry with cellular calcium imaging measurements of thalamocortical axons in awake behaving mice, we examined the impact of arousal and behavioral state on encoding of visual motion in the visual thalamus. We discovered that back-to-front visual motions elicits a robust behavioral response that shapes tunings of visual thalamic responses. Consistent with an arousal mechanism, the effects were pronounced during stillness and weak or absent during locomotor activity and under anesthesia. The impact on neuronal tuning was specific, biasing population response patterns in favor of back-to-front motion. The potent influence of visual motion on behavioral state dynamically affect sensory coding at early visual processing stages. Further research is required to reveal the circuitry and function of this novel mechanism.

neuroscience↗